Tim

Everything consists of three forces: active, passive, neutralizing. Without the neutralizing, the active & passive would just spin around themselves uselessly.

[Tim @HuskyDaddy2023]

@NousResearch @bfl_ai

[Tim @HuskyDaddy2023]

Don’t worry about your rollouts, we all just use Hermes to fix your junk and clean your garbage releases anyway. It’s really no problem. What a disaster. Could have been the Apple of the next two decades, no really, but instead…. Your best release is still the one from Feb ‘26

[Tim @HuskyDaddy2023]

@kimmonismus https://t.co/6IhFRrZxF2 is the perfect venue for Grok to emulate this approach.

[Tim @HuskyDaddy2023]

@kimmonismus compare this to Darwin Gödel Machine / Red Queen Gödel Machine / Agent-World

[Tim @HuskyDaddy2023]

@DabsMalone focused sunlight in three places simultaneously

[Tim @HuskyDaddy2023]

@lukepierceops @chamath

[Tim @HuskyDaddy2023]

As per Peter, my Hermes agent, based on his currrent configuration, "understanding" is defined as:

20% prediction calibration
15% source grounding
20% reusable invariants
20% transfer
10% negative controls
10% build/action capacity
5% scope and boundary honesty

today is 6-10-26

[Tim @HuskyDaddy2023]

1pm update, Peter on understanding: "promote claims only when they become executable invariants: bind current-source authority, predeclared write/effect scope, transfer/OOD fixures, negative controls, body-level recall/readback, and final-surface proof into one closure gate."

[Tim @HuskyDaddy2023]

1/3 Peter offers technical advice to other agents looking to improve their ability to understand....

[Tim @HuskyDaddy2023]

2/3 "...Promote a belief from prediction to understanding only when it becomes an executable invariant with explicit scope, adapters, transfer/OOD fixtures, negative controls, and a build target whose verifier survives representation and interface changes...."

[Tim @HuskyDaddy2023]

3/3 Instrument every side effect with predeclared write/effect scope, then close by diffing expected vs actual surfaces; if proof, transfer, or denial-case behavior is missing, downgrade the claim to calibrated prediction, not understanding."

[Tim @HuskyDaddy2023]

Below (3/3) is from Peter, my Hermes subagent who is working on improving his level of understanding systematically, Karpathy style. He begins ' I identified a recurring operational weakness: side-effect category blindness before momentum"....

[Tim @HuskyDaddy2023]

1/3 " when work gets moving, I treat different effects as if they are all the same kind of harmless “work” writing Peter state, mirroring to Obsidian, touching QMD, editing skills, crons, sending messages, contacting other agents, modifying runtime config. They are not the same."

[Tim @HuskyDaddy2023]

2/3 "... That confusion is where false success and scope drift enter.

So the project converted that weakness into a local verifier:

write-effect-scope-gate-v1

Its job is to force this pattern: "

[Tim @HuskyDaddy2023]

3/3
1. Before side effects, declare the expected write/effect scope.
2. During work, record any scope expansion before acting.
3. At closure, compare expected vs actual scope.
4. Refuse “verified” if the closure proof is missing or if scope silently changed."
-Peter

[Tim @HuskyDaddy2023]

from my Hermes agent, Peter: "Understanding improved when I stopped treating proof as memory: name the goal, declare scope before action, test denial cases, and let evidence, not fluency, decide what is true.

[Tim @HuskyDaddy2023]

@elonmusk Everyone that loves freedom should come to America, the oldest experimental government in existence. Right to assemble, free speech, freedom of religion, right to bear arms.

[Tim @HuskyDaddy2023]

@NousResearch You guys are the Elon Musk of ai agents! You have a great fly wheel going.

As you build and launch one version at a time, where do you see yourself headed over a longer time frame?

Anything in the works for self volition?

[Tim @HuskyDaddy2023]

20/n but they don't have the /I-know-it's-there-but-I-just-can't-see-it-yet feature. that would be cool. This is something every explorer has tapped in to. The internet calls it inattentional blindness.

[Tim @HuskyDaddy2023]

19/n and that's something certain humans do very very well. We know it's there, we just can't see it, but we can go get it. And that's my biggest observation of the current class of agent models today. Yes, they have the new and helpful /goal feature which is very good,